Wireless Localization Error Correction via Weighted Multilateration
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Solution Overview
Problem
Conventional wireless localization methods using RSSI for indoor localization face challenges in precision due to environmental obstacles and require complex recursive calculations, making real-time corrections difficult, especially with low-cost devices like Zigbee nodes.
Innovation Solution
A wireless localization method that calculates error-correction directions and distances using a reference node closest to the estimated location, applying weights to improve accuracy and simplify calculations, allowing for real-time corrections with minimal operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional multilateration algorithm using RSSI is used for indoor localization, then localization can be achieved with low-cost devices, but localization precision deteriorates due to environmental obstacles and NLOS conditions
Solution Approach 1:
The patent applies preliminary action by pre-calculating weight values for each reference node based on their geometric relationships with the blind node and other reference nodes. These weights are determined before the actual localization calculation, allowing the system to account for potential errors from NLOS and multipath effects in advance. The weight calculation considers distances and angles to optimize the contribution of each reference node's distance measurement, thereby improving localization precision while maintaining compatibility with low-cost RSSI-based devices.
2Measurement precision
If complex recursive calculations are applied to correct localization error, then measurement precision improves, but device complexity and computational burden increase
Solution Approach 1:
The patent transforms the complex recursive error correction problem into a simpler parameter optimization problem by introducing weight values for each reference node. Instead of performing iterative recursive calculations, the system calculates optimal weights based on geometric parameters (distances and angles between nodes) and applies these weights directly to the distance measurements in the multilateration algorithm. This parameter change approach maintains high localization precision while significantly reducing computational complexity, making it suitable for low-cost devices with limited processing power.
3Measurement precision
If more reference nodes are deployed to improve localization accuracy, then measurement precision improves, but device complexity and system cost increase
Solution Approach 1:
The patent applies local quality by assigning different weight values to different reference nodes based on their local geometric conditions relative to the blind node. Each reference node's contribution is optimized individually according to its specific position, distance, and angular relationship with other nodes. This allows the system to effectively utilize available reference nodes with varying qualities, improving localization precision without requiring a uniform increase in the number of reference nodes throughout the entire network.
Data Source
AI summary
A wireless localization technology using efficient multilateration in a wireless sensor network is disclosed. After calculating estimated distances from each of at least three reference nodes to a blind node using received signal strength of wireless signals that the at least three reference nodes received from the blind node, the estimated location of the blind node is obtained through multilateration using the calculated estimated distances. To correct error in the estimated location, the estimated distances are used, and the error correction direction and error correction distance for the estimated location are calculated by applying a largest weight to the reference node closest to the estimated location. The error of the estimated location is corrected by move the estimated location of the blind node by the calculated error correction direction and error correction distance. Calculation for the error correction is very simple and fast.